cd ../../../
exp_id="sparse_qahoi"

#backbone='resnet50'
backbone='swin-t'
dataset='vcoco'
dataset_path='data/v-coco'
addr="127.0.0.1"
port=1120
num_gpu=4
pretrained='params/SparseDETR/sparse_detr_swint_50-pre-2stage.pth'
#pretrained='params/SparseDETR/sparse_detr_r50_scrl_10-pre-2stage.pth'
#pretrained='pretrained/vcoco/vcoco_cdn_s.pth'
#pretrained='params/Detr/detr-r50-pre-2stage.pth'
#pretrained='logs/vcoco/hm_obj_verb_vis/stage1/checkpoint_best.pth'
#pretrained='params/ConditionalDetr/ConditionalDETR_r50-pre-2stage.pth'
#pretrained='params/DeformableDetr/r50_deformable_detr-pre-2stage.pth'
#resume='logs/vcoco/myhoi_no_hoi/stage1/checkpoint_20.pth'
output_dir=logs/$dataset/$exp_id/stage1/

export OMP_NUM_THREADS=1
python main.py \
--world_size $num_gpu \
--master_addr $addr \
--master_port $port \
--exp_id $exp_id \
--output_dir $output_dir \
--dataset_file $dataset \
--hoi_path $dataset_path \
--num_obj_classes 81 \
--num_verb_classes 29 \
--batch_size 4 \
--pretrained $pretrained \
--fpn \
--backbone $backbone \
--enc_layers 6 \
--dec_layers 6 \
--epochs 150 \
--lr_drop 120 \
--num_feature_levels 4 \
--num_queries 300 \
--dim_feedforward 1024 \
--set_cost_verb_class 1 \
--verb_loss_coef 1 \
--eff_query_init \
--eff_specific_head \
--rho=0.5 \
--with_box_refine \
--two_stage \
--use_enc_aux_loss \
--use_nms_filter

